Solution Blueprints¶
Additional AI solution patterns for IBM Z — covering generative AI, fraud detection, credit risk, health insurance, data preprocessing, and anti-money laundering. Each pattern walks you through building, deploying, and integrating an AI model into a business application with working code.
View all templates on GitHub →
Generative AI¶
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Document Intelligence with Spyre (Generative AI)
A reference implementation for running IBM Granite LLM inference on Red Hat AI Inference Server, leveraging the IBM Spyre Accelerator on IBM Z.
Fraud Detection¶
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Fraud Detection on IBM Z (z/OS)
Deploy an AI fraud detection model using open-source frameworks and Machine Learning for IBM z/OS (MLz). Covers the full lifecycle from data preparation through to production scoring.
Credit Risk Assessment¶
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Credit Risk Assessment on IBM Z (z/OS)
Build and deploy a credit risk scoring model using open-source frameworks and Machine Learning for IBM z/OS, with real-time scoring co-located with transactional data.
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Credit Risk Assessment on Linux on Z (Linux on Z)
Deploy a credit risk assessment model on IBM Linux on Z using open-source frameworks and IBM Z Accelerated for Triton Inference Server for containerized production serving.
Health Insurance Claims¶
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Health Insurance Claims on IBM Z (z/OS)
Build an AI model for health insurance claims processing using open-source frameworks and Machine Learning for IBM z/OS, deployed for real-time scoring on z/OS.
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Health Insurance Claims on Linux on Z (Linux on Z)
Deploy a health insurance claims model on IBM Linux on Z using open-source frameworks and IBM Z Accelerated for Triton Inference Server for containerized serving.
Data Preprocessing¶
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Data Preprocessing with IBM Z (z/OS)
Build an AI solution with a preprocessing pipeline on IBM Z using open-source frameworks and Machine Learning for IBM z/OS. Covers feature engineering, transformation, and production deployment.
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Data Preprocessing with Linux on Z (Linux on Z)
Build an AI solution with a preprocessing pipeline on IBM Linux on Z using open-source frameworks, Golang, and IBM Z Accelerated for Triton Inference Server for serving.
Anti-Money Laundering¶
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Anti-Money Laundering on IBM Z (z/OS)
Deploy an AML detection model using open-source frameworks and Machine Learning for IBM z/OS. Designed for real-time transaction monitoring and compliance workflows.
Additional Use Case Resources¶
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Advanced Credit Card Fraud Detection
See a full end-to-end solution blueprint — Advanced Credit Card Fraud Detection using an XGBoost and BERT ensemble on IBM z17.
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Understand the three AI entry points — Turnkey Solution, Select a Model, and Build Your Own — to identify the approach that best fits your organization.
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Follow the end-to-end AI lifecycle on IBM Z — from preparing data and training models to deploying, serving, and governing AI in production.
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Browse the full catalog of IBM Z AI products and tools to identify what fits your use case and entry point.